Formation of titania nanotube arrays by anodisation: DOE approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Large-Area Plasmonic Substrate of Silver-Coated Iron Oxide Nanorod Arrays for Plasmon-Enhanced Spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A hybrid method for the solution of a sparse power system matrices on vector computers

This paper describes a methodology for solving a linear system of equations on vector computer. The methodology combines direct and inverse factors. The decomposition and implementation of the direct solution in a CRAY Y-MPZE/232, and the performance results are discussed.

Maximizing Resource Sharing in WDM Mesh Networks With Path-Based Protection and Sparse OEO Regeneration

We propose a resource-sharing scheme that supports three kinds of sharing scenarios in a WDM mesh network with path-based protection and sparse OEO regeneration. Several approaches are used to maximize the sharing of wavelength-links and OEO regenerators.

Performance Analysis of Sparse Traffic Grooming in WDM Mesh Networks

Sparse traffic grooming is a practical problem to be addressed in heterogeneous multi-vendor optical WDM networks where only some of the optical cross-connects (OXCs) have grooming capabilities. Such a network is called as a sparse grooming network. The sparse grooming problem under dynamic traffic in optical WDM mesh networks is a relatively unexplored problem. In this work, we propose the maximize-lightpath-sharing multi-hop (MLS-MH) grooming algorithm to support dynamic traffic grooming in sparse grooming networks. We also present an analytical model to evaluate the blocking performance of the MLS-MH algorithm. Simulation results show that MLSMH outperforms an existing grooming algorithm, the shortest path single-hop (SPSH) algorithm. The numerical results from analysis show that it matches closely with the simulation. The effect of the number of grooming nodes in the network on the blocking performance is also analyzed.

Highly Sensitive Neurotransmitters Analysis at Platinum-Ultramicroelectrodes Arrays

An easy way to determine norepinephrine (NE) in biological fluid using a platinum ultramicroelectrode array (Pt-UMEAs) is described. Issues related to UME electrode surface treatment and characterizations are also addressed. At optimized experimental conditions the dynamic concentration range was 1.0 to 10.0 mu mol?L-1 with a detection limit of 40.5 nmol?L-1. The repeatability of current responses for injections of 5 mu mol?L-1 NE was evaluated to be 4.0?% (n=10). This approach obtained excellent sensitivity, a reliable calibration profile and stable electrochemical response for norepinephrine detection. The content of NE in urine samples without any preconcentration, purification, or pretreatment step, was successfully analyzed by the standard addition method using the Pt-UMEAs.

Anderson-like Transition for a Class of Random Sparse Models in d >= 2 Dimensions

We show that the Kronecker sum of d >= 2 copies of a random one-dimensional sparse model displays a spectral transition of the type predicted by Anderson, from absolutely continuous around the center of the band to pure point around the boundaries. Possible applications to physics and open problems are discussed briefly.

Vibro-Acoustography Beam Formation with Reconfigurable Arrays

In this work, we present a numerical study of the use of reconfigurable arrays (RCA) for vibro-acoustography (VA) beam formation. A parametric study of the aperture selection, number of channels, number of elements, focal distance, and steering parameters is presented to show the feasibility and evaluate the performance of VA imaging based on RCA. The transducer aperture was based on two concentric arrays driven by two continuous-wave or toneburst signals at slightly different frequencies. The mathematical model considers a homogeneous, isotropic, inviscid medium. The point-spread function of the system is calculated based on angular spectrum methods using the Fresnel approximation for rectangular sources. Simulations considering arrays with 50 x 50 to 200 x 200 elements with number of channels varying in the range of 32 to 128 are evaluated to identify the best configuration for VA. Advantages of two-dimensional and RCA arrays and aspects related to clinical importance of the RCA implementation in VA, such as spatial resolution, image frame rate, and commercial machine implementation, are discussed. It is concluded that RCA transducers can produce spatial resolution similar to confocal transducers and steering is possible in the elevational and azimuthal planes. Optimal settings for number of elements, number of channels, maximum steering, and focal distance are suggested for VA clinical applications. Furthermore, an optimization for beam steering based on the channel assignment is proposed for balancing the contribution of the two waves in the steered focus.

Insertional translocation of 15q25-q26 into 11p13 and duplication at 8p23.1 characterized by high resolution arrays in a boy with congenital malformations and aniridia

We report on a boy presenting submucous cleft palate, hydronephrosis, ventriculoseptal defect, aniridia, and developmental delay. Additional material on 11p13 was cytogenetically visible and array analyses identified a duplicated segment on 15q25-26 chromosome region; further, array analyses revealed a small deletion (49?kb) at 11p13 region involving the ELP4 gene and a duplication at 8p23.1. Results were confirmed with both molecular and molecular cytogenetics techniques. Possibilities for etiological basis of clinical phenotype are discussed. (c) 2012 Wiley Periodicals, Inc.

Morphology and topography analysis of mesoporous titania templated by micrometric latex sphere arrays

In this work, mesoporous titania is prepared by templating latex sphere arrays with four different sphere diameters at the micrometric scale (phi > 1 mu m). The mesoporous titania homogeneously covers the latex spheres and substrate, forming a thin coating characterized by N-2 adsorption isotherm, small angle X-rays scattering, atomic force, field emission and transmission electronic microscopies. Mesoporous titania has been templated into different shapes such as hollow particles and monoliths according to the amount of sol used to fill the voids of the close packed latex spheres. Titania topography strongly depends on the adsorption of polymeric segments over latex spheres surface, which could be decreased by changing the dimensions of latex spheres (phi = 9.5 mu m) generating a lamellar architecture. Thus, micrometric latex sphere arrays can be used to achieve new surface patterns for mesoporous materials via a fast and inexpensive chemical route for construction of functional devices in different technological fields such as energy conversion, inclusion chemistry and biomaterials. (C) 2011 Elsevier Inc. All rights reserved.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Paralelización de un algoritmo de ray tracing para arrays de mililentes

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)